Early-warning application for real-time detection of energy consumption anomalies in buildings. (15th April 2017)
- Record Type:
- Journal Article
- Title:
- Early-warning application for real-time detection of energy consumption anomalies in buildings. (15th April 2017)
- Main Title:
- Early-warning application for real-time detection of energy consumption anomalies in buildings
- Authors:
- Chou, Jui-Sheng
Telaga, Abdi S.
Chong, Wai K.
Gibson, G. Edward - Abstract:
- Abstract: Energy consumption data must be presented to office occupants to encourage them to save energy when in their office buildings. Therefore, this work develops an early warning application (EWA) that intelligently analyzes electricity consumption and provides a real-time visualization of anomalous consumption based on data from smart meters and sensors to various stakeholders. Although smart meters collect massive amounts of data from different sources, many systems cannot analyze and informatively present rapidly collected data. Accordingly, they do not motivate people to adopt energy-saving behaviors. The contribution of this study is to design an EWA architecture that visually presents real-time anomalous power consumption in an office space based on data that are obtained from various instruments (smart meters and sensors) to office occupants. The anomalous consumption of the EWA dashboard is designed to ensure that office occupants with limited technical skills understand the presented energy consumption data. The collected anomaly data provide post-occupancy information. Electricity consumption data from smart meters and sensors in a real office space are used to demonstrate the effectiveness of the proposed EWA. A building manager can use archived anomaly data to audit energy consumption, to produce an energy reduction policy, and to support a retrofitting strategy. Highlights: Building occupants should be notified of their energy consumption to encourageAbstract: Energy consumption data must be presented to office occupants to encourage them to save energy when in their office buildings. Therefore, this work develops an early warning application (EWA) that intelligently analyzes electricity consumption and provides a real-time visualization of anomalous consumption based on data from smart meters and sensors to various stakeholders. Although smart meters collect massive amounts of data from different sources, many systems cannot analyze and informatively present rapidly collected data. Accordingly, they do not motivate people to adopt energy-saving behaviors. The contribution of this study is to design an EWA architecture that visually presents real-time anomalous power consumption in an office space based on data that are obtained from various instruments (smart meters and sensors) to office occupants. The anomalous consumption of the EWA dashboard is designed to ensure that office occupants with limited technical skills understand the presented energy consumption data. The collected anomaly data provide post-occupancy information. Electricity consumption data from smart meters and sensors in a real office space are used to demonstrate the effectiveness of the proposed EWA. A building manager can use archived anomaly data to audit energy consumption, to produce an energy reduction policy, and to support a retrofitting strategy. Highlights: Building occupants should be notified of their energy consumption to encourage energy saving. This study designs a dashboard for presenting in real-time anomalous energy consumption. The architecture of an early-warning system is proposed and implemented. The developed smartphone application can be used by occupants with a limited technical background. This research contributes to the visually representation of the anomalous consumption of energy in an office space. … (more)
- Is Part Of:
- Journal of cleaner production. Volume 149(2017)
- Journal:
- Journal of cleaner production
- Issue:
- Volume 149(2017)
- Issue Display:
- Volume 149, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 149
- Issue:
- 2017
- Issue Sort Value:
- 2017-0149-2017-0000
- Page Start:
- 711
- Page End:
- 722
- Publication Date:
- 2017-04-15
- Subjects:
- Smart meter -- Anomalous consumption -- Feedback visualization -- Early warning -- Building energy monitoring -- Energy usage and policy
Factory and trade waste -- Management -- Periodicals
Manufactures -- Environmental aspects -- Periodicals
Déchets industriels -- Gestion -- Périodiques
Usines -- Aspect de l'environnement -- Périodiques
628.5 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09596526 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jclepro.2017.02.028 ↗
- Languages:
- English
- ISSNs:
- 0959-6526
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4958.369720
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